{"id":"W2416616485","doi":"10.1007/978-1-60327-101-1_11","title":"Neural Networks Predict Protein Structure and Function","year":2008,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Structural Genomics Consortium","funders":"National Institute of General Medical Sciences","keywords":"Artificial neural network; Computer science; ENCODE; Feedforward neural network; Artificial intelligence; Machine learning; Set (abstract data type); Protein function prediction; Types of artificial neural networks; Supervised learning; Protein structure prediction; Time delay neural network; Protein structure; Protein function; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001241533,0.0006658524,0.0005621754,0.0009195558,0.0002617457,0.0006817319,0.0006657626,0.000768858,0.001285217],"category_scores_gemma":[0.005565695,0.0003130662,0.000338472,0.0007749799,0.0003954117,0.001177258,0.0004316912,0.00098575,0.0008424734],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004890292,"about_ca_system_score_gemma":0.0004392285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002196247,"about_ca_topic_score_gemma":0.00240851,"domain_scores_codex":[0.9996725,0.0001021838,0.00002003471,0.00007091788,0.0001008388,0.00003358246],"domain_scores_gemma":[0.9985513,0.0009416349,0.000143065,0.00009651136,0.0002424715,0.00002501294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002011445,0.0001174177,0.009108048,0.0002087789,0.0001356249,0.00008295201,0.00004035132,0.6955203,0.01313569,0.01458511,0.005571302,0.2612933],"study_design_scores_gemma":[0.000006651227,0.0000131154,0.001151446,0.00001535483,0.00001155725,0.00001452778,0.000005660796,0.983686,0.003931267,0.01030412,0.0008512198,0.000008994202],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1695928,0.004607802,0.8145928,0.00124648,0.0002751425,0.00007613206,0.001085285,0.003101769,0.005421735],"genre_scores_gemma":[0.7787035,0.004022573,0.210325,0.00028472,0.0002052563,0.0001642079,0.001630679,0.0001576362,0.004506325],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002196247,"threshold_uncertainty_score":0.006565928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008454072518830746,"score_gpt":0.2986411057929527,"score_spread":0.290187033274122,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}